Performance Evaluation of Fuzzy Logic and Back Propagation Neural Network for Hand Written Character Recognition

Fuzzy c-mean is one of the efficient tools used in character recognition.Back propagation neural network is another powerful that may be used in such field.A comparison between fuzzy c-mean and BP neural network classifiers are presented in this research to obtain the performance of both classifiers.The comparison was based on recognition efficiency; this efficiency was evaluated as the ratio of the number of assigned characters with unknown one to the number of character set related to that character.The fuzzy C-mean and BP neural network algorithms were tested on a set of hand written and machine printed dataset named Chars74K dataset using Matlab (2016 b) programming language and the result was that neural network classifier gave 82% recognition efficiency while fuzzy c -mean gave 78%.Neural network classifier is more superior than fuzzy C-mean in recognition due to the limitations of processing time of fuzzy C-mean that requires smaller image size and eventually this will cause less efficiency..